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Understanding functional diversity of brain regions and brain networks

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Understanding functional diversity of brain regions and brain networks

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  1. Understanding functional diversity of brain regions and brain networks Luiz Pessoa Department of Psychology Maryland Neuroimaging Center University of Maryland, College Park

  2. Joint work with • Michael Anderson: Franklin & Marshall • LucinaUddin: Stanford/University of Miami • Josh Kinnison: University of Maryland

  3. Structure-function mapping “fear” F1 F2 F3 F4 A1 A2 A3 A4 amygdala One-to-one mapping

  4. Structure-function mapping “fear” “value” F1 F2 F3 F4 A1 A2 A3 A4 amygdala ventral striatum Many-to-manymapping

  5. Structure-function mapping Emotion Cognition Motivation Perception Action … ?

  6. Functional fingerprint Regions Passingham et al. (2002) Understanding brain regions via functional repertoires: multidimensional

  7. Functional fingerprint Task domains (ontology) BrainMap NeuroSynth Understanding brain regions via functional repertoires: imaging data

  8. Functional fingerprint Understanding brain regions via functional repertoires: imaging data

  9. Functional diversity index Anderson, Kinnison, and Pessoa (2013), Neuroimage Regions will be more or less “diverse” Use Shannon Entropy

  10. Voxelwise diversity H

  11. Functional diversity: networks

  12. Functional diversity: networks Network fingerprint

  13. Brain networks Toro et al. (2008) Fronto-parietal “attention” network (co-activation of BrainMap data)

  14. Functional fingerprint

  15. Brain networks Toro et al. (2008) Cingulo-parietal “resting-state” network (co-activation of BrainMap data)

  16. Functional fingerprint

  17. Understanding insula function Deen et al. (2010)

  18. Understanding insula function Determine co-activation partners (using NeuroSynth) Uddin et al. (submitted)

  19. Understanding insula function Determine co-activation partners (using NeuroSynth) Uddin et al. (submitted)

  20. Understanding insula function Determine co-activation partners (using NeuroSynth) Uddin et al. (submitted)

  21. Understanding insula function Common fingerprint All insula sub-sectors are highly diverse (cf. tripartite cognitive-affective-interoceptive scheme)

  22. Understanding insula function “Specific” fingerprint components mean Sadness Happiness Fear … Phonology Working memory Reasoning … Left dorsal anterior insula

  23. Understanding insula function “Specific” fingerprint components Dorsal Posterior Ventral “Cognitive” “Affective”

  24. Brain networks Toro et al. (2008) Fronto-parietal: “attention” Cingulo-opercular: “resting-state” Dorsal attention: “endogenous attention” Ventral attention: “exogenous attention” Fronto-parietal: “rapid adaptive control” Cingulo-opercular: “stable set control” List goes on and on…

  25. How to compare networks? Task positive Task negative

  26. How to compare networks • Evaluate whether two sets (i.e., networks) of fingerprints are drawn from the same parent distribution • “Statistical energy” (Aslan and Zech, 2005)

  27. How to compare networks X Y Statistical energy

  28. Comparing networks Task-positive (co-activation; Toro et al. 2008) vs. Dorsal attention (resting-state; Yeo et al. 2011) Task-positive vs. Task-negative (co-activation data) Permutation testing of ϕXY

  29. Are brain networks assortative? Assortativity: “like connects with like”

  30. How to compare networks X Z Y • Statistical energy • “Functional distance” • Pairs of regions within a network • Pairs of regions between networks

  31. Are brain networks assortative? Networks

  32. Are brain networks assortative? “Dorsal attention”

  33. Are brain networks assortative? “Ventral attention”

  34. Are brain networks assortative? Dis-assortative “Default network”

  35. Are brain networks assortative? Dis-assortative “Default network”: should fragment into several subnetworks

  36. Summary Characterize contributions of individual brain regions and networks without using singular task-bound functional attributions Described quantitative property of networks – functional assortativity – that can be useful in understanding the functional and compositional similarities and differences between networks

  37. Structure-function mapping Behaviors Cognitive Neural computations NC1 NC2 NC3 NC4 A1 A2 A3 A4 Brain areas Network 1 Network 2 Network 3 Pessoa (2008), Nature Reviews Neuroscience

  38. Michael Anderson Josh Kinnison LucinaUddin Collaborators National Institute of Mental Health emotioncognition.org